PyPy seems to be the one real contender for fast Python. ZipPy was super interesting academic work but unfortunately does not seem to be going anywhere.
I am not surprised that a silicon valley company stopped sponsoring this. 3 years of silicon valley salary is quite an investment in small gains of CPU perf.
Look at the Ruby sphere, where competitive implementations have taken millions in man hours and still most run on MRI.
The Oracle Labs Truffle approach and the PyPy RPython ones seem to be the only way to deliver a compatible, fast language implementation at a cost that a community and or enterprise can bear.
Both Truffle and PyPy are long running projects, but both offered more than just faster CPU times. i.e. see related work on accelerating SQL using RPython and most likely behind closed doors for Truffle.
Truffle also has a sane compatibility story for Ruby and similar ZipPy would have offered it for Python.
I am not surprised that a silicon valley company stopped sponsoring this. 3 years of silicon valley salary is quite an investment in small gains of CPU perf.
Look at the Ruby sphere, where competitive implementations have taken millions in man hours and still most run on MRI.
The Oracle Labs Truffle approach and the PyPy RPython ones seem to be the only way to deliver a compatible, fast language implementation at a cost that a community and or enterprise can bear.
Both Truffle and PyPy are long running projects, but both offered more than just faster CPU times. i.e. see related work on accelerating SQL using RPython and most likely behind closed doors for Truffle.
Truffle also has a sane compatibility story for Ruby and similar ZipPy would have offered it for Python.